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Autonomous robot with evolving algorithm based on biological systems

  • Evolutionary Robotics
  • Conference paper
  • First Online:
Evolvable Systems: From Biology to Hardware (ICES 1996)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1259))

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Abstract

This paper describes an evolvable system that has a computational model of basal ganglia and hippocampus which have close relation to the generation and management of memory and movement faculty in our brain. We also describe its application to the design of learnable autonomous mobile robots. From a view point of Evolvable System, first we argue how the particular functions of basal ganglia and hippocampus work for memory and movement. Next a computational model of basal ganglia and hippocampus is presented as a specific type of evolvable systems, and how this model can be used for the design of learnable robots is described. Then we make our actually constructed robot learn, using the implemented model, four fundamental behavior tasks such as those insects learn in their baby stages. It follows with the analysis of the learned behavior. Finally, we discuss the significance of our research.

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References

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Tetsuya Higuchi Masaya Iwata Weixin Liu

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© 1997 Springer-Verlag Berlin Heidelberg

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Yamamoto, J., Anzai, Y. (1997). Autonomous robot with evolving algorithm based on biological systems. In: Higuchi, T., Iwata, M., Liu, W. (eds) Evolvable Systems: From Biology to Hardware. ICES 1996. Lecture Notes in Computer Science, vol 1259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63173-9_49

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  • DOI: https://doi.org/10.1007/3-540-63173-9_49

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63173-6

  • Online ISBN: 978-3-540-69204-1

  • eBook Packages: Springer Book Archive

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